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11th International Conference on Electrical and Electronics engineering, ICEEE 2024

作者： Ur Rahman, Ehab Ashiku, Lirim Dagli, Cihan Bo, Rui Missouri University of Science and Technology Department of Electrical and Computer Engineering RollaMO United States Missouri Universtity of Science and Technology Engineering Management and Systems Engineering RollaMO United States

ISBN: (纸本)9798350362541

Smart grids are at risk of cyber-attacks due to more connected devices being introduced. Different kinds of attacks may incur different consequences in the operation of smart grids. Attackers have identified different vulnerable points in smart grid operations and have developed malicious stealthy attacks to disrupt the operation of physical systems. In this paper we have formulated the power system cyber security problem as a five-dimensional optimization problem. A general framework is developed using the system of system explorer tool providing a defensive solution to the vulnerable points of a smart grid prone to malicious attacks. An optimal meta-architecture composed of defensive system constituents is achieved using Genetic algorithm (GA) and fuzzy inference system providing a solution to ensure cybersecurity of power system operations. © 2024 IEEE.

关键词： Cyber attacks

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An improved real time detection of data poisoning attacks in deep learning vision systems

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Discover Artificial Intelligence 2022年第1期2卷 1-17页

作者： Raghavan, Vijay Mazzuchi, Thomas Sarkani, Shahram Department of Engineering Management and Systems Engineering The George Washington University 2121 I St NW WashingtonDC20052 United States

The practice of using deep learning methods in safety critical vision systems such as autonomous driving has come a long way. As vision systems supported by deep learning methods become ubiquitous, the possible security threats faced by these systems have come into greater focus. As it is with any artificial intelligence system, these deep neural vision networks are first trained on a data set of interest, once they start performing well, they are deployed to a real-world environment. In the training stage, deep learning systems are susceptible to data poisoning attacks. While deep neural networks have proved to be versatile in solving a host of challenges. These systems have complex data ecosystems especially in computer vision. In practice, the security threats when training these systems are often ignored while deploying these models in the real world. However, these threats pose significant risks to the overall reliability of the system. In this paper, we present the fundamentals of data poisoning attacks when training deep learning vision systems and discuss countermeasures against these types of attacks. In addition, we simulate the risk posed by a real-world data poisoning attack on a deep learning vision system and present a novel algorithm MOVCE—Model verification with Convolutional Neural Network and Word Embeddings which provides an effective countermeasure for maintaining the reliability of the system. The countermeasure described in this paper can be used on a wide variety of use cases where the risks posed by poisoning the training data are similar. © The Author(s) 2022.

关键词： Learning systems

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Advanced Liveness Detection for Facial Recognition: Combating Fake Faces with Reflectivity Analysis 10

Advanced Liveness Detection for Facial Recognition: Combatin...

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10th IEEE Smart World Congress, SWC 2024

作者： Liu, Xinpeng Wang, Wen Singapore Management University School of Engineering Singapore Xi'an Jiaotong-Liverpool University Department of Intelligence Systems China

ISBN: (纸本)9798331520861

Facial recognition technology has become integral to daily life, facilitating processes such as online payments, smart door locks, and mobile phone unlocking, while enhancing security. However, its accuracy can be compromised by variations in illumination and action scale, making it vulnerable to high-fidelity fake face attacks. This project addresses these issues by identifying the differing reflectivity of human skin, video images, and fake face headgear under light. Utilizing spatio-temporal domain characteristics of facial key points, a novel face action liveness detection algorithm was developed. This algorithm integrates motion trajectory, historical data, and skin color information to improve liveness detection. The project processes facial video to extract reflective layers at key points, using this data to train a model capable of distinguishing real faces from fake ones, thereby improving the robustness of facial recognition systems. © 2024 IEEE.

关键词： Face recognition

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Public Healthcare Informatics for COVID-19 from Social Media Data 46

Public Healthcare Informatics for COVID-19 from Social Media...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Kumar, Vishwa V. Sahoo, Avimanyu Kumar, Ritika Loyd, Nicholas Industrial & Systems Engineering and Engineering Management United States The University of Alabama in Huntsville Department of Electrical and Computer Engineering United States North Alabama Medical Center FlorenceAL United States

ISBN: (纸本)9798350371499

The COVID-19 pandemic has profoundly affected various facets of society. This research explores the discourse on social media, specifically "X"(Twitter), to understand public sentiment and needs regarding healthcare supply chain challenges, such as the availability of testing kits, oxygen supplies, and hospital beds, during the pandemic. By identifying pertinent opinionated keyphrases and employing advanced natural language processing (NLP) techniques, we sifted through over 3.9 million tweets to collect health informatics. The content of these tweets is analyzed to investigate the word trends and sentiments. The extracted sentiments were then organized into ten distinct categories using the K-means clustering method that pointed out top-ten healthcare supply needs. The findings underscore the value of social media as a tool for gathering timely and actionable insights on healthcare supply chain logistics, offering critical data for effective response strategies during health crises. © 2024 IEEE.

关键词： COVID-19

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Enhancing Communication Accessibility:UrSL-CNN Approach to Urdu Sign Language Translation for Hearing-Impaired Individuals

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Computer Modeling in engineering & Sciences 2024年第10期141卷 689-711页

作者： Khushal Das Fazeel Abid Jawad Rasheed Kamlish Tunc Asuroglu Shtwai Alsubai Safeeullah Soomro Department of Computer Engineering Modeling Electronics and Systems EngineeringUniversity of CalabriaRende Cosenza87036Italy Department of Information Systems University of Management and TechnologyLahore54770Pakistan Department of Computer Engineering Istanbul Sabahattin Zaim UniversityIstanbul34303Turkey Department of Software Engineering Istanbul Nisantasi UniversityIstanbul34398Turkey Department of Computer Science COMSATS University IslamabadLahore CampusLahore54700Pakistan Faculty of Medicine and Health Technology Tampere UniversityTampere33720Finland Department of Computer Science College of Computer Engineering and Sciences in Al-KharjPrince Sattam Bin Abdulaziz UniversityP.O.Box 151Al-Kharj11942Saudi Arabia Second Department of Computer Science College of Engineering and ComputingGeorge Mason UniversityFairfaxVA 4418USA

Deaf people or people facing hearing issues can communicate using sign language(SL),a visual *** works based on rich source language have been proposed;however,the work using poor resource language is still *** other SLs,the visuals of the Urdu Language are *** study presents a novel approach to translating Urdu sign language(UrSL)using the UrSL-CNN model,a convolutional neural network(CNN)architecture specifically designed for this *** existingworks that primarily focus on languageswith rich resources,this study addresses the challenge of translating a sign language with limited *** conducted experiments using two datasets containing 1500 and 78,000 images,employing a methodology comprising four modules:data collection,pre-processing,categorization,and *** enhance prediction accuracy,each sign image was transformed into a greyscale image and underwent noise *** analysis with machine learning baseline methods(support vectormachine,GaussianNaive Bayes,randomforest,and k-nearest neighbors’algorithm)on the UrSL alphabets dataset demonstrated the superiority of UrSL-CNN,achieving an accuracy of ***,our model exhibited superior performance in Precision,Recall,and F1-score *** work not only contributes to advancing sign language translation but also holds promise for improving communication accessibility for individuals with hearing impairments.

关键词： Convolutional neural networks Pakistan sign language visual language

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Cooperative Donation programs in Supply Chains With Non-Governmental Organizations (NGOs)

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IEEE Transactions on engineering management 2024年 71卷 574-585页

作者： Pahlevani, Mahsa Choi, Tsan-Ming Heydari, Jafar Xu, Xiaoyan University of Tehran School of Industrial Engineering College of Engineering Tehran*** Iran Dalhousie University Department of Industrial Engineering HalifaxNSB3H 4R2 Canada National Taiwan University Department and Graduate Institute of Business Administration College of Management Taipei10617 Taiwan The Hong Kong Polytechnic University Department of Industrial and Systems Engineering Hong Kong Hong Kong

Today, corporate social responsibility (CSR) is known as a critical element of supply chain (SC) operations. In this article, we analytically study an SC coordination problem with social efforts for charity. The proposed SC includes one retailer and one manufacturer in which the manufacturer gives donations to a nongovernmental organization (NGO) in two forms, namely a lump sum amount plus a per-sold-item donation amount. While CSR efforts have been considered as an abstract concept in prior studies, this article contributes to the literature by specifically exploring an SC with an NGO in the form of two types of donations as CSR activities. The problem is first modeled under a decentralized decision-making setting in which each member focuses on its own profit. The second model is developed under the centralized decision-making structure in which the whole SC profit under the centralized scenario is improved. To achieve Pareto-improving channel coordination, a cooperative donation program using a combined 'wholesale price and cost-sharing' contract is proposed. Our analytically proven results demonstrate that the proposed SC coordination contract can achieve Pareto improvement. Moreover, we prove that the NGO receives more donations under the proposed contract. Therefore, the proposed contract is beneficial to both the SC members and the NGO. In the extended model, we investigate the case under the endogenous 'low/high pricing regimes' and reveal that the main findings remain robust. Managerial insights and implications are discussed. © 1988-2012 IEEE.

关键词： Supply chains

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A Review of the Multiple Criteria for the Design of Resilient Buildings

A Review of the Multiple Criteria for the Design of Resilien...

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2024 IEEE International Conference on Technology management, Operations and Decisions, ICTMOD 2024

作者： Abdulmaksoud, Sara Akram, Fayqa Ahmed, Vian Engineering Systems Management American University of Sharjah Sharjah United Arab Emirates American University of Sharjah Department of Industrial Engineering Sharjah United Arab Emirates

ISBN: (纸本)9798350367355

Climate change and its repercussions, namely meteorological hazards such as floods, are occurring more severely and frequently compared to any point in history, due to anthropogenic activities such as the increase in urbanization rates. These floods inevitably have adverse impacts on the built environment and have resulted in immense financial damage and a sizable number of fatalities globally. Henceforth, resilience against floods is of paramount significance in the built environment. Specifically, 'resilience' in the design of buildings has become a growing theme and is deemed a powerful tool for survivability against the current climate crisis. Similarly, the United Arab Emirates (UAE) is also becoming vulnerable to meteorological disasters such as floods, which are aggravated by the substantial urbanization occurring. Therefore, the adoption of resilient design strategies in building design is a mandatory undertaking in the UAE. For the successful implementation of resilience in buildings, a thorough understanding of what resilience is in a building design context is vital. However, in the UAE, there is still no clear understanding of what resilience is in the construction industry or what criteria are essential for designing resilient buildings, and this is attributed to the lack of tools that could assist in the implementation of resilient building design strategies. Designing for resilience is a significant challenge and therefore, scholars have emphasized the importance of implementing suitable decision support tools to guide the stakeholders in the construction industry to successfully achieve favorable resilient design decisions. Accordingly, upon reviewing the previously conducted research and frameworks that discuss the various applications of design strategies for resilient buildings to counteract the risk of catastrophes such as floods, this paper aims to underpin the criteria that define the application of resilience in the different building componen

关键词： Building components

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Challenges in Securing UAV IoT Framework: Future Research Perspective

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IEEE Transactions on Network and Service management 2025年第3期22卷 2607-2629页

作者： Aljumah, Abdullah Ahanger, Tariq Ahamed Ullah, Imdad Prince Sattam Bin Abdulaziz University College of Computer Engineering and Sciences Saudi Arabia CoBA Prince Sattam Bin Abdulaziz University Department of Management Information Systems Saudi Arabia The University of Sydney School of Computer Science Faculty of Engineering SydneyNSW2006 Australia

Unmanned Aerial Vehicles (UAVs) offer the immense capability for allowing novel applications in a variety of domains including security, military, surveillance, medicine, and traffic monitoring. The prevalence of UAV systems is due to the collaboration and accomplishment of tasks efficiently and effectively. UAVs embedded with camcorders, GPS receivers, and wireless sensors propose enormous promise in realizing the Internet of Things (IoT) service delivery in vast domains. It results in establishing an airborne field of the IoT when empowered with communication protocols of LTE, 4G, and 5G/6G networks. However, numerous difficulties must be addressed before UAVs may be used effectively namely privacy, security, and administration. Conspicuously, in the current article, novel UAV-specific domains enabled by IoT and 5G/6G technology are explored. Moreover, the presented technique assesses sensor requirements and provides an overview of fleet management systems that address aerial networking, privacy, and security concerns. Furthermore, a framework based on the IoT-5G/6G aspect is proposed which can be deployed over UAVs. Finally, in a heterogeneous computational platform, the proposed framework provides a complete IoT architecture that enables secure UAVs. © 2004-2012 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Adoption of cognitive computing decision support system in the assessment of health-care policymaking

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Journal of systems and Information Technology 2023年第4期25卷 395-439页

作者： Behera, Rajat Kumar Bala, Pradip Kumar Panigrahi, Prabin Kumar Dasgupta, Shilpee A. School of Computer Engineering Kalinga Institute of Industrial Technology Bhubaneswar India Department of Information Systems and Business Analytics Indian Institute of Management Ranchi Ranchi India Department of Information Systems Indian Institute of Management Indore Indore India Department of General Management Indian Institute of Management Ranchi Ranchi India

Purpose: Despite technological advancements to enhance patient health, the risks of not discovering the correct interactions and trends in digital health are high. Hence, a careful policy is required for health coverage tailored to needs and capacity. Therefore, this study aims to explore the adoption of a cognitive computing decision support system (CCDSS) in the assessment of health-care policymaking and validates it by extending the unified theory of acceptance and use of technology model. Design/methodology/approach: A survey was conducted to collect data from different stakeholders, referred to as the 4Ps, namely, patients, providers, payors and policymakers. Structural equation modelling and one-way ANOVA were used to analyse the data. Findings: The result reveals that the behavioural insight of policymakers towards the assessment of health-care policymaking is based on automatic and reflective systems. Investments in CCDSS for policymaking assessment have the potential to produce rational outcomes. CCDSS, built with quality procedures, can validate whether breastfeeding-supporting policies are mother-friendly. Research limitations/implications: Health-care policies are used by lawmakers to safeguard and improve public health, but it has always been a challenge. With the adoption of CCDSS, the overall goal of health-care policymaking can achieve better quality standards and improve the design of policymaking. Originality/value: This study drew attention to how CCDSS as a technology enabler can drive health-care policymaking assessment for each stage and how the technology enabler can help the 4Ps of health-care gain insight into the benefits and potential value of CCDSS by demonstrating the breastfeeding supporting policy. © 2023, Emerald Publishing Limited.

关键词： Decision support systems

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ADVANCING AUTONOMOUS ROBOTICS: INTEGRATING MECANUM WHEELS, LIDAR, AND SLAM FOR ENHANCED MOBILITY AND NAVIGATION THROUGH STUDENT INVOLVEMENT

ADVANCING AUTONOMOUS ROBOTICS: INTEGRATING MECANUM WHEELS, L...

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ASME 2024 International Mechanical engineering Congress and Exposition, IMECE 2024

作者： Chiou, Richard Y. Vasudevan, Nijanthan Kavitha, Arjuna Karthikeyan Senthilvel Tseng, Tzu-Liang Department of Engineering Leadership and Society Engineering Technology Program Drexel University PhiladelphiaPA United States Department of Industrial Manufacturing and Systems Engineering University of Texas at El Paso El PasoTX United States

ISBN: (纸本)9780791888650

This study unveils an advanced autonomous mobile robot (AMR) designed as a practical educational module for students, featuring Mecanum wheels, LiDAR, and integrated through a comprehensive SLAM algorithm, all within the framework of the Robot Operating System (ROS). The AMR's use of Mecanum wheels affords it unparalleled agility and the capability to maneuver omnidirectionally in intricate settings. LiDAR technology enhances the robot's ability to generate detailed spatial maps, crucial for real-time navigation and obstacle avoidance. Through experimental validation in a controlled laboratory environment, the AMR demonstrated superior navigational accuracy and adaptability to evolving conditions. This hands-on educational approach not only underlines the robot's effectiveness in navigating real-world challenges but also positions it as an adaptable solution for future automation tasks, emphasizing the potential for its application across a broad spectrum of industrial and commercial fields. Copyright © 2024 by ASME.

关键词： SLAM robotics

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